CN116029008A - A file generation method, device, terminal device and storage medium - Google Patents

Abstract

The embodiment of the present application discloses a file generation method, device, terminal equipment, and storage medium, wherein the method includes: importing the DBC file/LDF file of the target model; Read to determine the data frame included in the corresponding CAN signal/LIN signal; edit the target data frame in the data frame so that the target data frame is used as the medium for sending and/or receiving the target signal; according to the edit As a result, a JSON file corresponding to the target protocol and the target model is generated. Through the above method, there is no need to manually write glue codes to realize the connection between models, the coupling is low, it is easy to realize modularization, and it can be compatible and adapted to various hardware.

Description

A file generation method, device, terminal device and storage medium

technical field

The present application relates to the technical field of hardware-in-the-loop simulation, and in particular to a file generation method, device, terminal equipment and storage medium.

Background technique

Hardware in the loop, HIL (Hardware-in-the-Loop), that is, hardware in the loop. The hardware-in-the-loop system, HIL system, is a hardware-in-the-loop simulation test system. It uses a real-time processor to run a simulation model to simulate the running state of the controlled object. It is connected to the ECU under test through the I/O interface, and the ECU under test is Comprehensive and systematic testing.

The hardware-in-the-loop test system generally consists of a simulation model, the IO hardware of the bench, and the object to be tested (such as ECU). The simulation model is generally generated by modeling software, which is generally a mathematical model. It has nothing to do with itself, but because of the hardware-in-the-loop test, the signal of the object under test must be given to the simulation model through the IO hardware board of the bench. Therefore, it is necessary to establish a direct connection between the simulation model and the simulation model, and between the simulation model and the IO hardware of the bench.

In the prior art, establishing a direct connection between simulation models is realized by writing glue codes. Although incompatible models can be connected and work properly through glue code. However, this method has strong coupling, is not easy to achieve modularization, and cannot be compatible with various hardware.

Contents of the invention

Embodiments of the present application provide an HIL-based file generation method, device, terminal device, and storage medium, so as to solve the above-mentioned problems in the background technology.

In the first aspect, the embodiment of the present application provides a method for generating a file, the method comprising:

Import the DBC file/LDF file of the target model;

Read the DBC file/LDF file according to the preset target protocol, and determine the data frame contained in the corresponding CAN signal/LIN signal;

editing the target data frame in the data frame, so that the target data frame is used as a medium for sending and/or receiving a target signal;

Generate a JSON file corresponding to the target protocol and the target model according to the editing result.

In the second aspect, the embodiment of the present application also provides a file generation device, the device includes:

The import module is used to import the DBC file/LDF file of the target model;

A determining module, configured to read the DBC file/LDF file according to a preset target protocol, and determine the data frame contained in the corresponding CAN signal/LIN signal;

An editing module, configured to edit the target data frame in the data frame, so that the target data frame can be used as a medium for sending and/or receiving a target signal;

A generating module, configured to generate a JSON file corresponding to the target protocol and the target model according to the editing result.

In a fourth aspect, the embodiment of the present application further provides a storage medium, wherein a plurality of instructions are stored in the storage medium, and the instructions are adapted to be loaded by a processor to execute the above-mentioned file generation method.

The file generation method in the embodiment of the present application reads the imported DBC file/LDF file according to the preset target protocol, determines the data frame contained in the corresponding CAN signal/LIN signal, and performs the target data frame in the data frame Editing is performed so that the target data frame can be used as a medium for sending and/or receiving target signals, and a JSON file corresponding to the target protocol and target model is generated according to the editing results. Through the above method, there is no need to manually write glue codes to realize the connection between models, the coupling is low, it is easy to realize modularization, and it can be compatible and adapted to various hardware.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings that need to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application. For those skilled in the art, other drawings can also be obtained based on these drawings without any creative effort.

FIG. 1 is a flow chart of a method for generating a file provided by an embodiment of the present application.

FIG. 2 is a user interface diagram for importing a DBC file provided by the embodiment of the present application.

Fig. 3 is a user interface diagram for importing LDF files provided by the embodiment of the present application.

FIG. 4 is a user interface diagram of a display list provided by an embodiment of the present application.

Fig. 5a is a diagram of a user interface for model editing provided by an embodiment of the present application.

Fig. 5b is another user interface diagram of model editing provided by the embodiment of the present application.

Fig. 6 is a user interface diagram of a grouping configuration provided by an embodiment of the present application.

Fig. 7 is a user interface diagram of a model configuration provided by the embodiment of the present application.

Fig. 8 is a user interface diagram of a model configuration provided by the embodiment of the present application.

Fig. 9 is another user interface diagram of a model configuration provided by the embodiment of the present application.

Fig. 10 is a schematic structural diagram of a file generating device provided by an embodiment of the present application.

Fig. 11 is another schematic structural diagram of a file generation device provided by an embodiment of the present application.

FIG. 12 is a schematic structural diagram of a terminal device provided by an embodiment of the present application.

Detailed ways

The following will clearly and completely describe the technical solutions in the embodiments of the application with reference to the drawings in the embodiments of the application. Apparently, the described embodiments are only some of the embodiments of the application, not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts belong to the scope of protection of this application.

In the description of the embodiments of the present application, it should be understood that the terms "first" and "second" are only used for descriptive purposes, and cannot be interpreted as indicating or implying relative importance or implicitly indicating the indicated technical features. quantity. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of said features. In the description of the embodiments of the present application, "plurality" means two or more, unless otherwise specifically defined.

The following description is given to enable any person skilled in the art to make and use the application. In the following description, details are set forth for purposes of explanation. It should be understood that one of ordinary skill in the art would recognize that the present application may be practiced without these specific details. In other instances, well known procedures have not been described in detail to avoid obscuring the description of the embodiments of the present application with unnecessary detail. Therefore, the present application is not intended to be limited to the illustrated embodiments, but to be consistent with the broadest scope consistent with the principles and features disclosed in the embodiments of the present application.

Embodiments of the present application provide a file generation method, device, terminal device, and storage medium, which will be described in detail below.

Please refer to Figure 1, Figure 1 is a flow chart of a file generation method provided in the embodiment of the present application, including the following:

101. Import the DBC file/LDF file of the target model.

102. Read the DBC file/LDF file according to a preset target protocol, and determine a data frame contained in a corresponding CAN signal/LIN signal.

103. Edit the target data frame in the data frame, so that the target data frame is used as a medium for sending and/or receiving a target signal.

Set the scene test requirements, determine the target model that needs to generate model instances according to the scene test requirements, retrieve the DBC file/LDF file of the target model from the database, import the DBC file/LDF file into the hardware-in-the-loop simulation test system, and use the hardware-in-the-loop The loop simulation test system generates the JSON file of the DBC file/LDF file, compiles the JSON file, and then generates the final target model of the target model, that is, generates a model instance of the target model, and performs hardware-in-the-loop simulation testing through the model instance. Optionally, the database for storing files may include a DBC database and an LDF database, where DBC files are stored in the DBC database, and LDF files are stored in the LDF database.

When the imported file is a DBC file, the corresponding target model is a DBC model. When the imported file is an LDF file, the corresponding target model is an LDF model.

Input the file name of the DBC file/LDF file of the target model in the button name column of the user interface of the hardware-in-the-loop simulation test system, and then click the import button on the user interface to realize the import of the file. Or, select the DBC file/LDF file of the target model from the database through a selection operation on the user interface of the hardware-in-the-loop simulation test system, and then click the import button on the user interface to realize file import.

After the file is imported, the corresponding interface is displayed on the user interface of the hardware-in-the-loop simulation test system. As shown in Figure 2, for the user interface where the DBC file of the target model is selected but not imported, the DBC file can be imported by clicking the import DBC button on the user interface. As shown in Figure 3, for the user interface where the LDF file of the target model is selected but not imported, the LDF file can be imported by clicking the import LDF button on the user interface.

After the DBC file/LDF file is imported, the hardware-in-the-loop simulation test system reads the imported DBC file/LDF file, and determines the data frame contained in the CAN signal/LIN signal corresponding to the file. The CAN signal corresponds to the DBC file, and the LIN signal corresponds to the LDF file.

Exemplarily, the DBC file of the target model is imported into the hardware-in-the-loop simulation test system, and the hardware-in-the-loop simulation test system reads the DBC file, and determines the data frame contained in the CAN signal through the corresponding CAN bus information.

As shown in FIG. 4 , on the user interface displaying the data frames included in the CAN signal or the data frames included in the LIN signal, the ID, name and type of each included data frame are displayed in the form of a display list. After setting the output and/or input of the target data frame in the data frame, click or check a certain target data frame, and the signal name and frame type of the target data frame will be displayed accordingly. The frame type can include sending frames and receive frames. If a target data frame is set to output the signal, click or check the target data frame, and the displayed frame type is a send frame. If a target data frame is set to input the signal, click or check the target data frame, and the displayed frame type is a receive frame. If a target data frame is set to output and input signals, click or check the target data frame, and the displayed frame types are send frame and receive frame. Edit the data frame, that is, set the model test node. The way to set it is to first select the model DBC file. After the DBC file is selected, all the parameters described in the DBC file will be listed in the node selection box to be tested. CAN network node, and then select a CAN network node as the test node. After the test node is selected, the receiving frame and sending frame of the node will be automatically listed in the node receiving frame and node sending frame list. After confirmation, the selected test node will be used. The data frame is used for subsequent model editing. After the test node is selected, the system will automatically configure the corresponding sending group for the sending frame of the selected node.

Edit and set the input and output of the target data frame in the data frame, as shown in Figure 5a-5b, the edit setting method can include setting to send frame, set to receive frame, set to send and receive frame, add to group and from group delete etc. Among them, an example of adding to a packet is adding a plurality of transmission frames to one transmission packet. In addition, the editing setting method can also include removing, and the removed data frame does not participate in subsequent model editing. When setting, it can be set according to the scene test requirements and the characteristic information of the data frame.

If the editing setting method for a target data frame is sending, then the target data frame is an output frame. Correspondingly, if the editing setting mode of a target data frame is receiving, the target data frame is an input frame. Or, if the editing setting mode of a certain target data frame is sending and receiving, then the target data frame is an input and output frame.

Optionally, in some embodiments, the target data frame in the data frame is edited so that the target data frame is used as the medium for sending and/or receiving the target signal, including: creating a task group according to the scenario test requirements, and setting the task The transmission function of the group edits the target data frame in the data frame according to the transmission function, adds the edited target data frame to the task group, and sends and/or receives the target signal through the task group.

As the imported file is a DBC file, creating a task group is actually creating a group of CAN signals. Correspondingly, setting the transmission function of the task group is actually setting the target signal for data frame group transmission, and setting the group for inputting the target signal /output/input output. After removing the to-be-discarded data frame of the CAN signal and editing the target data frame of the CAN signal, it is clear that the data frame retained by the CAN signal is one of the input frame, output frame or input-output frame. According to the set transmission function, determine the matching target data frame from the reserved and edited data frames, add the target data frame to the task group, that is, add the target data frame to the group, so as to realize the input/output/ input Output.

Optionally, each data frame can have multiple signals after being expanded, and the characteristic information of the corresponding data frame can be obtained through the information of these signals, so that according to the characteristic information and scene test requirements, the edited data frame can be retained and completed Matching target dataframes determined in are added to the task group.

As shown in Figure 6, the user interface in Figure 6 shows the editing of the grouping configuration, corresponding to the above-mentioned task group creation, after the task group is created, the matching target data frame can be added to the task group, and can The unmatched target data frames in the task group are deleted from the task group, or the task groups that have added target data frames or have not added target data frames can be deleted. After the task group is created, the system sets a group name for the task group according to a preset naming rule, or manually sets the group name of the task group. In addition to setting the group name of the task group, the group identifier of the task group may also be set, that is, the group ID of the task group. After the matching target data frame is added to the task group, the associated task group and each target data frame included are identified by grouping, so as to facilitate query and management of the task group.

For the imported file is an LDF file, create a task group and set the transmission function of the task group, actually create a task that meets the preset target, set the target signal for task transmission, and set the task to input/output/input the target signal Output and set task type. Among them, the task types include main task, initialization task and conflict resolution task.

Optionally, in some embodiments, if the imported file is an LDF file, create a task group according to the scenario test requirements, and set the transfer function of the task group, including: obtaining a configurable model generation mode and simulation corresponding to the LDF file node, and obtain the LIN network node described in the LDF file, determine the target generation mode of the target model from the model generation mode according to the scene test requirements, and determine the target generation mode from the LIN network node according to the target generation mode The simulation node of the target model creates a task group of the target model according to the target generation mode and the simulation node, and sets the transfer function of the task group.

Among them, after determining the target generation mode, determine the simulated nodes from the LIN network nodes described in the LDF file, and the LIN network nodes are divided into master nodes and slave nodes.

As shown in Figure 7, after the LDF file is imported, a mode selection can be created. On the user interface corresponding to the creation mode selection, configurable model generation modes and simulation nodes are displayed. The model generation modes include master mode, slave mode and master-slave Mode, the simulation node is set according to the actual needs, defined by the LDF file. Among them, the analog node is a communication node defined by the LDF file, which is the master node or slave node in the LIN network nodes. Determine the simulation node according to the target generation mode, including: select the master node in the LIN network node described in the LDF file as the simulation node in the master mode, and edit the scheduling task of the master node at the same time; select one of the LIN network nodes described in the LDF file in the slave mode The slave node is used as a simulation node, and the sending and receiving frames of the node can be edited; in the master-slave mode, one of the LIN network nodes described in the LDF file is selected as a simulation node, and the scheduling tasks of the master node can be edited at the same time. Select one of the model generation modes on the user interface as the target generation mode, and select the master node or slave node in the LIN network nodes as the simulation node according to the target generation mode. After selecting the target generation mode and simulation node, click the confirm button to realize setting the target generation mode and simulation node of the target model corresponding to the LDF file.

As shown in FIG. 8 , the user interface in FIG. 8 includes a message sending column and a message receiving column, and the message sending column and the message receiving column are used to configure sending/receiving messages. It can be considered that the message sending column is used to create a task with the function of sending a signal, and this task may correspond to a target data frame of an output signal, or may correspond to multiple target data frames of an output signal. The message receiving column is used to create a task with the function of receiving a signal. This task can correspond to the target data frame of one input signal, or can correspond to the target data frames of multiple input signals.

When setting, you can edit and set the target data frame contained in the LIN signal of the LDF file, and the editing and setting methods can include sending, receiving, and sending and receiving. Edit and set the target data frame contained in the LIN signal to determine the input and output of the target data frame, thereby forming the port of the corresponding target model. After editing and setting the target data frame, according to the scene test requirements, create a task group in the message sending column or message receiving column, and add one or more target data frames after editing and setting to the task column, so that each task Groups can send and/or receive signals of interest.

After the task group is created in the message sending column or message receiving column, the created task group can be modified and deleted. And, set the name of the task group, the task ID, and the sender/receiver of the target signal. Among them, when the task group is created in the message sending column, the target data frame contained in the task group is used as the sender to send the target signal, and the receiver of the target signal is used as the receiver. Among them, when the task group is created in the message receiving column, the target data frame contained in the task group is used as the receiver to receive the target signal, and the sender of the target signal is used as the sender.

Optionally, in some embodiments, after adding the edited target data frame to the task group and sending and/or receiving the target signal through the task group, it also includes: determining the Task type, the task type includes main task, initialization task and conflict resolution task, and the task group is added to the schedule matching the task type. Among them, the main task is the main scheduling task of the master node, which is composed of multiple main scheduling tables, which are used to schedule the transmission of data frames on the bus when the model is running, and the multiple main scheduling tables of the main task are executed in order. The initialization task contains an initialization schedule table to execute the initialization task. The conflict resolution task includes multiple conflict resolution schedules, which are bound to the event-triggered data frame. When the event-triggered data frame conflicts, the corresponding conflict resolution schedule is executed.

As shown in FIG. 9 , the user interface corresponding to the scheduling table in FIG. 9 displays three types of task bars: a main task bar, an initial task bar and a conflict resolution task bar. After creating a task group and setting the transfer function of the task group, the task group can be added to the task column matching its task type in the scheduling table according to the scene creation requirements, that is, the task group is added to the corresponding task column in the matching scheduling table .

After the task group is added to the corresponding task column in the matching schedule, in the subsequent processing process, according to the preset task processing rules, the task groups in the main task column, initial task column and conflict resolution task column to process.

104. Generate a JSON file corresponding to the target protocol and the target model according to the editing result.

Since the file is read according to the preset target protocol when reading the DBC file/LDF file, the data frame contained in the corresponding signal is determined after the DBC file/LDF file is read, and the target in the data frame The data frame is edited so that the edited target data frame sends and/or receives the target signal, thereby generating a corresponding JSON file. The file protocol of the generated JSON file is the target protocol, and the generated JSON file corresponds to the target model. Optionally, the target protocol may be a Schema protocol.

The target protocol can be understood as a protocol that can define at least the following content:

How to read the data frame in the CAN signal in the DBC file; for example, what data frame should be read from where;

How to read the data frame in the LIN signal in the LDF file; for example, what data frame should be read from where;

The relationship between the various information that can be edited for the data frame in CAN signal and LIN signal and the code in the corresponding JSON file; for example, where and how should the edited information (that is, the information in the editing result) be written in the JSON file At least one of describing information and the like.

In addition, the target protocol can also define configurable information, non-configurable information, and format conditions of configurable information required by models of different model categories for simulation models other than LDF models and DBC models.

Furthermore, the method may also include:

Determine the first JSON file of the simulation model of the non-target model (i.e. non-LDF model, non-DBC model), wherein the first JSON file is used to define at least one configuration required to generate the model file package of the simulation model Configuration information and non-configurable information; for example, determine the model category of the target model; generate the first JSON file according to the target protocol and the model category of the simulation model, wherein the protocol is used to define the model requirements of different model categories Configurable information to be configured, non-configurable information, and format conditions of the configurable information;

Configuring the content of the configurable information defined in the first JSON file to generate a second JSON file of the target model, wherein the second JSON file is used to describe all configurable information and non-configurable information;

Compiling and generating a model file package of the simulation model based on the second JSON file.

The simulation model can be, for example, analog output processing model, analog input model, digital output model, digital input model, PWM signal input model, PWM signal output model, Ethernet model, timer model, socket model, custom model and any of the third-party models.

Furthermore, through the target protocol, how to use DBC files and LDF files (and other files and information corresponding to simulation models) can be standardized and pre-defined, and finally form a JSON file that can be compiled, which effectively improves the understanding of DBC models and LDF models. (and other models) generation efficiency, reducing the workload of developers, among them, only need to call the protocol to meet the generation requirements, no need to manually write a large number of codes for the generation requirements of the model, and at the same time, it can help to standardize The method ensures the validity of the generated DBC model and LDF model.

Optionally, in some embodiments, if the imported file is a DBC file, after generating the JSON file corresponding to the target protocol and the target model according to the editing results, it also includes: compiling the JSON file to generate the final target of the target model model, and generate the schedulable object of the final target model corresponding to the task group, register the schedulable object to the target system, so that the schedulable object can be called. Among them, the schedulable object is an object that can be scheduled by the target system, which is represented as an executable function in the target system, and the scheduling means executing the executable function, and the schedulable object can be activated and executed by the target system event.

The generated JSON file is a file with no parameters configured. It is necessary to configure and compile the parameters of the generated JSON file to generate a model file package that can be parsed and run by the bench. The final target model of the target model is generated through the model file package, that is, the generated target A model instance of the model and produces a schedulable object of the final target model corresponding to the created task group. Register the schedulable object into the MRTD system (Model Runtime Driven System), so that the schedulable object can be activated and executed by the target system event of the target system corresponding to the final target model or other models.

Optionally, in some embodiments, after registering the schedulable object in the target system so that the schedulable object can be called, it further includes: when receiving a system event corresponding to the schedulable object, calling the schedulable object from the target system The scheduling object is used to send and/or receive the target signal corresponding to the system event through the schedulable object.

System events can be events that occur in the final target model, or events that occur in other models connected to the MRTD system.

The file generation method of the embodiment of the present application includes: importing the DBC file/LDF file of the target model; reading the DBC file/LDF file according to the preset target protocol, and determining the data contained in the corresponding CAN signal/LIN signal frame; edit the target data frame in the data frame, so that the target data frame is used as the medium for sending and/or receiving the target signal; generate JSON corresponding to the target protocol and the target model according to the editing result document. Through the method of the embodiment of the present application, there is no need to manually write glue codes to realize the connection between the models, the coupling is low, it is easy to realize modularization, and it can be compatible and adapted to various hardware.

In one embodiment, in the host computer, the connection relationship of data ports between models can also be determined through the following process:

Determine the data ports available for connection in the target simulation model to be connected (the above is any one or both of the mentioned target model and simulation model);

determining port description information of the target data port;

According to the port description information and preset port connection rules, the connection relationship between the target data ports is determined, so that when the target simulation model is working, signal transmission is performed based on the connection relationship. The process of determining the connection relationship can be implemented in response to the user's operation on the corresponding interface. In this process, the result of the user's operation can be limited, adjusted or verified based on the port description information and port connection rules.

In the above process, in addition to ensuring that the data types in the port description information of the connected data port need to be the same, and the data transmission direction needs to be corresponding; in one example, the target data can be determined according to the port description information Whether the port has a queue attribute; then according to the port connection rules, determine that the target data port that does not have the queue attribute in the connection relationship and is an input port is only connected to one target data port. Furthermore, if the connection relationship realized by the user's operation does not match, the confirmation of the connection relationship can be prohibited or canceled, and an abnormality of the connection relationship can also be prompted.

The queue attribute can also be understood as a queue identifier, which is used to identify whether the corresponding port allows multiple target data ports to be connected. Further, it can also be understood as: whether such a mechanism is designed in the corresponding simulation model, that is, based on the queue , a mechanism for sequentially processing data input (or output) from different connected data ports.

In one embodiment, after determining the two target simulation models that need to be connected, if the two target simulation models are assumed to be the first target simulation model and the second target simulation model, the target data port and its Connection relationship:

Acquiring one or more pieces of empirical information on the simulation model of the first target simulation model and the simulation model of the second target simulation model; the empirical information represents a connection mode that has occurred in the data port between the two types of models in the past;

If there are multiple pieces of experience information, the number of occurrences of each piece of experience information can be counted; then based on the number of times, the candidate connection relationship can be prompted in the interface, for example, the connection relationship can be described, and then displayed in descending order of the number of times Furthermore, the final connection relationship may be determined in response to the user's operation on the suggested connection relationship, that is, the connection operation mentioned above may be the user's operation on the recommended connection relationship.

Through the above methods, the connection experience of the past connection relationship can be used for reference to improve the efficiency of the connection, and at the same time, avoid or reduce the mistakes and omissions of the engineers who are still inexperienced when connecting.

In a further example, each piece of experience information can also be configured with a corresponding scene identification, which is used to identify the characteristics of the test scene, such as the test scene of the chassis domain controller, the test scene of the smart driving domain controller Scenarios and the like, the features of the scenarios are not limited to domain-based distinctions, for example, they may also include the manufacturer and purpose of the controller under test, and so on.

Furthermore, in the process of acquiring one or more pieces of experience information of the two types of models, only the experience information whose scenario identifier is completely or partially identical to the currently tested scenario may be acquired.

Furthermore, connection records with strong correlation can be applied to this test, and it is helpful to ensure the recommended connection. In particular, it can be adapted to changing and changing test tasks and test requirements in the cluster test process applied to HIL to improve efficiency.

Please refer to FIG. 10. FIG. 10 is a schematic structural diagram of a file generation device provided by an embodiment of the present application. The file generation device 200 includes the following modules:

The import module 201 is used to import the DBC file/LDF file of the target model.

The determining module 202 is configured to read the DBC file/LDF file according to the preset target protocol, and determine the data frame included in the corresponding CAN signal/LIN signal.

The editing module 203 is configured to edit the target data frame in the data frame according to the scene test requirement, so that the target data frame can be used as a medium for sending and/or receiving target signals.

The generating module 204 is configured to generate a JSON file corresponding to the target protocol and the target model according to the editing result.

Optionally, the file generation device 200 may also include the following modules:

The list generation module is used to generate a corresponding display list based on the data frame.

The removal module is configured to determine the data frame to be discarded in the data frame, and remove the data frame to be discarded from the display list.

Wherein, the list generating module is executed after the above-mentioned determining module 202 .

Optionally, the editing module 203 may include the following submodules:

The first sub-module is created, which is used to create a task group according to the scenario test requirements, and set the transmission function of the task group.

The frame editing sub-module is used to edit the target data frame in the data frame according to the transmission function.

The frame adding submodule is used to add the edited target data frame to the task group, and send and/or receive the target signal through the task group.

Optionally, corresponding to the settings of the above-mentioned first creating submodule, frame editing submodule and frame adding submodule, the file generation device 200 may further include the following modules:

The model generating module is used to compile the JSON file, generate the final target model of the target model, and generate a schedulable object of the final target model corresponding to the task group.

The registration module is used to register the schedulable object to the target system, so that the schedulable object can be called.

The calling module is configured to call the schedulable object from the target system when the system event corresponding to the schedulable object is received, and send and/or receive the target signal corresponding to the system event through the schedulable object.

Optionally, if the file imported by the import module 201 is an LDF file, the above-mentioned first creation submodule may include the following submodules:

The obtaining submodule is used to obtain the configurable model generation mode corresponding to the LDF file, and obtain the LIN network nodes described in the LDF file.

The first determination sub-module is used to determine the target generation mode of the target model from the model generation modes according to the scene test requirements.

The second determination sub-module is used to determine the simulation nodes of the target model from the LIN network nodes according to the target generation mode.

The second creation sub-module is used to create the task group of the target model according to the target generation mode and the simulation node, and set the transfer function of the task group.

Optionally, corresponding to the settings of the acquisition submodule, the first determination submodule, the second determination submodule and the second creation submodule, the file generation device 200 may further include the following modules:

The task determination module is used to determine the task type of the task group according to the transmission function, and the task type includes a main task, an initialization task and a conflict resolution task;

The task adding module is used to add the task group to the schedule matching the task type.

Wherein, the task determining module is executed after the above-mentioned frame adding submodule.

Optionally, the file generating apparatus 200 in the embodiment of the present application may also include other modules and sub-modules, which will not be repeated here.

The file generation device 200 of the embodiment of the present application includes: an import module 201, which is used to import the DBC file/LDF file of the target model; a determination module 202, which is used to read the DBC file/LDF file according to the preset target protocol Get, determine the data frame that corresponding CAN signal/LIN signal comprises; Edit module 203, be used for editing the target data frame in described data frame, make described target data frame send and/or receive as target signal Media; generating module 204, configured to generate a JSON file corresponding to the target protocol and the target model according to the editing result. Through the device of the embodiment of the present application, there is no need to manually write glue codes to realize the connection between the models, the coupling is low, it is easy to realize modularization, and it can be compatible and adapted to various hardware.

Please refer to FIG. 11. FIG. 11 is another schematic structural diagram of a file generation device provided by an embodiment of the present application. The file generation device 200 includes a memory 120, one or more processors 180, and one or more application programs, wherein the one or a plurality of application programs are stored in the memory 120 and configured to be executed by the processor 180; For example, the structure and connection relationship of the above components can be as follows:

The memory 120 can be used to store applications and data. The application programs stored in the memory 120 include executable codes. Applications can be composed of various functional modules. The processor 180 executes various functional applications and steps of the file generation method by running the application program stored in the memory 120 . In addition, the memory 120 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices. Correspondingly, the memory 120 may further include a memory controller to provide the processor 180 with access to the memory 120 .

The processor 180 is the control center of the device. It uses various interfaces and lines to connect various parts of the entire terminal. By running or executing the application program stored in the memory 120 and calling the data stored in the memory 120, various functions of the device are executed. function and process data for overall monitoring of the installation. Optionally, the processor 180 may include one or more processing cores; preferably, the processor 180 may integrate an application processor and a modem processor, wherein the application processor mainly processes operating systems, user interfaces, and application programs, etc. .

Specifically, in this embodiment, the processor 180 loads the executable code corresponding to the process of one or more application programs into the memory 120 according to the following instructions, and the processor 180 runs the executable code stored in the memory 120. applications to achieve various functions:

Import the DBC file/LDF file of the target model;

Read the DBC file/LDF file according to the preset target protocol, and determine the data frame contained in the corresponding CAN signal/LIN signal;

editing the target data frame in the data frame, so that the target data frame is used as a medium for sending and/or receiving a target signal;

Generate a JSON file corresponding to the target protocol and the target model according to the editing result.

In some embodiments, after the determination of the data frame contained in the corresponding CAN signal/LIN signal, the method further includes:

generating a corresponding display list based on the data frame;

Determine the data frames to be discarded in the data frames, and remove the data frames to be discarded from the display list.

In some embodiments, the editing of the target data frame in the data frame, so that the target data frame is used as a medium for target signal transmission and/or reception, includes:

Create a task group according to the scenario test requirements, and set the transmission function of the task group;

Editing the target data frame in the data frame according to the transmission function;

The edited target data frame is added to the task group, and the target signal is sent and/or received through the task group.

In some embodiments, if the imported file is a DBC file, after the JSON file corresponding to the target protocol and the target model is generated according to the editing result, the method further includes:

Compiling the JSON file, generating a final target model of the target model, and generating a schedulable object of the final target model corresponding to the task group;

The schedulable object is registered with the target system so that the schedulable object can be called.

In some embodiments, after registering the schedulable object with the target system so that the schedulable object can be called, the method further includes:

When a system event corresponding to the schedulable object is received, the schedulable object is called from the target system, and the target signal corresponding to the system event is sent and/or received through the schedulable object.

In some embodiments, if the imported file is an LDF file, the task group is created according to the scenario test requirements, and the transfer function of the task group is set, including:

Obtain a configurable model generation mode corresponding to the LDF file, and obtain the LIN network nodes described in the LDF file;

Determining the target generation mode of the target model from the model generation modes according to the scenario test requirements;

determining simulation nodes of the target model from the LIN network nodes according to the target generation mode;

A task group of the target model is created according to the target generation mode and the simulation node, and a transmission function of the task group is set.

In some embodiments, after adding the edited target data frame to the task group and sending and/or receiving the target signal through the task group, the method further includes:

determining a task type of the task group according to the transfer function, where the task type includes a main task, an initialization task, and a conflict resolution task;

Add the task group to the schedule matching the task type.

The embodiment of the present application also provides a terminal device. The terminal device may be a server, a smart phone, a computer, a tablet computer or the like.

Please refer to FIG. 12 . FIG. 12 is a schematic structural diagram of a terminal device provided in an embodiment of the present application. The terminal device 1200 can be used to implement the method for generating a file provided in the above embodiment. The terminal device 1200 may be a smart phone or a tablet computer.

As shown in Figure 12, a terminal device 1200 may include an RF (Radio Frequency, radio frequency) circuit 110, a memory 120 including one or more (only one is shown in the figure) computer-readable storage medium, an input unit 130, a display unit 140, a sensor 150, an audio circuit 160, a transmission module 170, a processor 180 including one or more (only one is shown in the figure) processing cores, a power supply 190 and other components. Those skilled in the art can understand that the structure of the terminal device 1200 shown in FIG. 12 does not constitute a limitation on the terminal device 1200, and may include more or less components than those shown in the figure, or combine certain components, or different components. layout. in:

The RF circuit 110 is used to receive and send electromagnetic waves, realize mutual conversion between electromagnetic waves and electrical signals, and communicate with communication networks or other devices. The RF circuit 110 may include various existing circuit elements for performing these functions, such as antennas, radio frequency transceivers, digital signal processors, encryption/decryption chips, Subscriber Identity Module (SIM) cards, memory, and the like. The RF circuit 110 can communicate with various networks such as the Internet, intranet, wireless network, or communicate with other devices through the wireless network.

The memory 120 can be used to store software programs and modules, such as program instructions/modules corresponding to the file generation method in the above-mentioned embodiments, and the processor 180 executes various functional applications and file generation by running the software programs and modules stored in the memory 120 steps of the method. The memory 120 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 120 may further include a memory that is remotely located relative to the processor 180, and these remote memories may be connected to the terminal device 1200 through a network. Examples of the aforementioned networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The input unit 130 can be used to receive input numbers or character information, and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control. Specifically, the input unit 130 may include a touch-sensitive surface 131 and other input devices 132 . The touch-sensitive surface 131, also referred to as a touch screen or a touchpad, can collect user touch operations on or near it (for example, the user uses any suitable object or accessory such as a finger or a stylus on the touch-sensitive surface 131 or near the touch-sensitive surface 131), and drive the corresponding connection device according to the preset program. Optionally, the touch-sensitive surface 131 may include two parts, a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch orientation, detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, and sends it It is converted into contact coordinates and then sent to the processor 180, and can receive and execute commands sent by the processor 180. In addition, the touch-sensitive surface 131 can be implemented in various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch-sensitive surface 131 , the input unit 130 may also include other input devices 132 . Specifically, other input devices 132 may include, but are not limited to, one or more of physical keyboards, function keys (such as volume control keys, switch keys, etc.), trackballs, mice, joysticks, and the like.

The display unit 140 can be used to display information input by or provided to the user and various graphical user interfaces of the terminal device 1200. These graphical user interfaces can be composed of graphics, text, icons, videos and any combination thereof. The display unit 140 may include a display panel 141. Optionally, the display panel 141 may be configured in the form of LCD (Liquid Crystal Display, liquid crystal display), OLED (Organic Light-Emitting Diode, organic light-emitting diode), and the like. Further, the touch-sensitive surface 131 may cover the display panel 141, and when the touch-sensitive surface 131 detects a touch operation on or near it, the touch operation is sent to the processor 180 to determine the type of the touch event, and then the processor 180 determines the type of the touch event according to the touch operation. According to the type of control event, a corresponding visual output is provided on the display panel 141. Although in FIG. 12 , the touch-sensitive surface 131 and the display panel 141 are used as two independent components to realize input and output functions, in some embodiments, the touch-sensitive surface 131 and the display panel 141 can be integrated to realize input. and output functions.

The terminal device 1200 may further include at least one sensor 150, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display panel 141 according to the brightness of the ambient light, and the proximity sensor may turn off the display panel 141 when the terminal device 1200 moves to the ear. and/or backlighting. As a kind of motion sensor, the gravitational acceleration sensor can detect the magnitude of acceleration in various directions (generally three axes), and can detect the magnitude and direction of gravity when it is stationary, and can be used for applications that recognize the attitude of mobile phones (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition-related functions (such as pedometer, tap), etc.; as for other sensors such as gyroscope, barometer, hygrometer, thermometer, and infrared sensor that can also be configured on terminal device 1200, here No longer.

The audio circuit 160 , the speaker 161 and the microphone 162 can provide an audio interface between the user and the terminal device 1200 . The audio circuit 160 can transmit the electrical signal converted from the received audio data to the loudspeaker 161, and the loudspeaker 161 converts it into an audio signal output; After being received, it is converted into audio data, and then the audio data is processed by the output processor 180, and then sent to another terminal through the RF circuit 110, or the audio data is output to the memory 120 for further processing. The audio circuit 160 may also include an earplug jack to provide communication between an external earphone and the terminal device 1200 .

The terminal device 1200 can help the user to send and receive e-mails, browse the web, access streaming media, etc. through the transmission module 170 (such as a Wi-Fi module), and it provides users with wireless broadband Internet access. Although FIG. 12 shows the transmission module 170, it can be understood that it is not an essential component of the terminal device 1200, and can be completely omitted as required without changing the essence of the invention.

The processor 180 is the control center of the terminal device 1200, and uses various interfaces and lines to connect various parts of the entire mobile phone, by running or executing software programs and/or modules stored in the memory 120, and calling data stored in the memory 120 , execute various functions and process data of the terminal device 1200, so as to monitor the mobile phone as a whole. Optionally, the processor 180 may include one or more processing cores; in some embodiments, the processor 180 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface and applications, etc., and the modem processor mainly handles wireless communications. It can be understood that the foregoing modem processor may not be integrated into the processor 180 .

The terminal device 1200 also includes a power supply 190 for supplying power to various components. In some embodiments, the power supply can be logically connected to the processor 180 through the power management system, so as to implement functions such as discharge management and power consumption management through the power management system. The power supply 190 may also include one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

Although not shown, the terminal device 1200 may also include a camera (such as a front camera, a rear camera), a Bluetooth module, etc., which will not be repeated here. Specifically in this embodiment, the display unit 140 of the terminal device 1200 is a touch screen display, and the terminal device 1200 also includes a memory 120 and one or more programs, wherein one or more programs are stored in the memory 120, and One or more programs configured to be executed by one or more processors 180 include steps for:

Import the DBC file/LDF file of the target model;

Read the DBC file/LDF file according to the preset target protocol, and determine the data frame contained in the corresponding CAN signal/LIN signal;

editing the target data frame in the data frame, so that the target data frame is used as a medium for sending and/or receiving a target signal;

Generate a JSON file corresponding to the target protocol and the target model according to the editing result.

In some embodiments, after the determination of the data frame contained in the corresponding CAN signal/LIN signal, the method further includes:

generating a corresponding display list based on the data frame;

Determine the data frames to be discarded in the data frames, and remove the data frames to be discarded from the display list.

In some embodiments, the editing of the target data frame in the data frame, so that the target data frame is used as a medium for target signal transmission and/or reception, includes:

Create a task group according to the scenario test requirements, and set the transmission function of the task group;

Editing the target data frame in the data frame according to the transmission function;

The edited target data frame is added to the task group, and the target signal is sent and/or received through the task group.

In some embodiments, if the imported file is a DBC file, after the JSON file corresponding to the target protocol and the target model is generated according to the editing result, the method further includes:

Compiling the JSON file, generating a final target model of the target model, and generating a schedulable object of the final target model corresponding to the task group;

The schedulable object is registered with the target system so that the schedulable object can be called.

In some embodiments, after registering the schedulable object with the target system so that the schedulable object can be called, the method further includes:

When a system event corresponding to the schedulable object is received, the schedulable object is called from the target system, and the target signal corresponding to the system event is sent and/or received through the schedulable object.

In some embodiments, if the imported file is an LDF file, the task group is created according to the scenario test requirements, and the transfer function of the task group is set, including:

Obtain a configurable model generation mode corresponding to the LDF file, and obtain the LIN network nodes described in the LDF file;

Determining the target generation mode of the target model from the model generation modes according to the scenario test requirements;

determining simulation nodes of the target model from the LIN network nodes according to the target generation mode;

A task group of the target model is created according to the target generation mode and the simulation node, and a transmission function of the task group is set.

In some embodiments, after adding the edited target data frame to the task group and sending and/or receiving the target signal through the task group, the method further includes:

determining a task type of the task group according to the transfer function, where the task type includes a main task, an initialization task, and a conflict resolution task;

Add the task group to the schedule matching the task type.

An embodiment of the present application further provides a storage medium, in which a computer program is stored, and when the computer program is run on a computer, the computer executes the file generation method described in any one of the above embodiments.

It should be noted that, for the file generation method described in this application, ordinary testers in the field can understand that all or part of the process of realizing the file generation method described in the embodiment of this application can be completed by controlling related hardware through computer programs , the computer program may be stored in a computer-readable storage medium, such as stored in a memory of a terminal device, and executed by at least one processor in the terminal device, and the execution process may include the file generation method as described in The flow of the embodiment. Wherein, the storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM, ReadOnly Memory), a random access memory (RAM, Random Access Memory), etc.

For the file generating device in the embodiment of the present application, each functional module may be integrated into one processing chip, each module may exist separately physically, or two or more modules may be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of software function modules. If the integrated modules are implemented in the form of software function modules and sold or used as independent products, they can also be stored in a computer-readable storage medium, such as read-only memory, magnetic disk or optical disk.

The file generation method, device, terminal device, and storage medium provided in the embodiments of the present application have been introduced in detail above. In this paper, specific examples are used to illustrate the principle and implementation of the application. The description of the above embodiments is only used to help understand the method and core idea of the application; meanwhile, for those skilled in the art, according to the application Thoughts, specific implementation methods and application ranges all have changes. In summary, the content of this specification should not be construed as limiting the application.

Claims (10)

1. A method for generating files, characterized in that the method comprises: Import the DBC file/LDF file of the target model; Read the DBC file/LDF file according to the preset target protocol, and determine the data frame contained in the corresponding CAN signal/LIN signal; editing the target data frame in the data frame, so that the target data frame is used as a medium for sending and/or receiving a target signal; Generate a JSON file corresponding to the target protocol and the target model according to the editing result. 2. The file generation method according to claim 1, wherein, after the data frame that the corresponding CAN signal/LIN signal comprises, the method also includes: generating a corresponding display list based on the data frame; Determine the data frames to be discarded in the data frames, and remove the data frames to be discarded from the display list. 3. The file generating method according to claim 1, wherein the target data frame in the data frame is edited so that the target data frame is used as a medium for target signal transmission and/or reception, include: Create a task group according to the scenario test requirements, and set the transmission function of the task group; Editing the target data frame in the data frame according to the transmission function; The edited target data frame is added to the task group, and the target signal is sent and/or received through the task group. 4. The file generating method according to claim 3, wherein, if the imported file is a DBC file, after the JSON file corresponding to the target protocol and the target model is generated according to the editing result, the Methods also include: Compiling the JSON file, generating a final target model of the target model, and generating a schedulable object of the final target model corresponding to the task group; The schedulable object is registered with the target system so that the schedulable object can be called. 5. The file generation method according to claim 4, characterized in that, after registering the schedulable object to the target system so that the schedulable object can be called, the method further comprises: When a system event corresponding to the schedulable object is received, the schedulable object is called from the target system, and the target signal corresponding to the system event is sent and/or received through the schedulable object. 6. The file generation method according to claim 3, wherein if the imported file is an LDF file, the task group is created according to the scene test requirements, and the transfer function of the task group is set, including: Obtain a configurable model generation mode corresponding to the LDF file, and obtain the LIN network nodes described in the LDF file; Determining the target generation mode of the target model from the model generation modes according to the scenario test requirements; determining simulation nodes of the target model from the LIN network nodes according to the target generation mode; A task group of the target model is created according to the target generation mode and the simulation node, and a transmission function of the task group is set. 7. The file generating method according to claim 6, characterized in that, adding the edited target data frame to the task group, the target signal is sent and/or through the task group After receiving, the method also includes: determining a task type of the task group according to the transfer function, where the task type includes a main task, an initialization task, and a conflict resolution task; Add the task group to the schedule matching the task type. 8. A file generation device, characterized in that the device comprises: The import module is used to import the DBC file/LDF file of the target model; A determining module, configured to read the DBC file/LDF file according to a preset target protocol, and determine the data frame contained in the corresponding CAN signal/LIN signal; An editing module, configured to edit the target data frame in the data frame according to the scene test requirements, so that the target data frame can be used as a medium for sending and/or receiving target signals; A generating module, configured to generate a JSON file corresponding to the target protocol and the target model according to the editing result. 9. A terminal device, characterized by comprising a memory and a processor, the memory is used to store instructions and data, and the processor is used to execute the file generating method according to any one of claims 1-7. 10. A storage medium, wherein a plurality of instructions are stored in the storage medium, and the instructions are adapted to be loaded by a processor to execute the file generation method according to any one of claims 1-7.

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